| 2023 | BIBE | An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. | Abhinav Sattiraju, Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun |
| 2023 | ICASSP | Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers. | Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun |
| 2022 | BIBE | An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. | Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun |
| 2022 | BIBE | Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models. | Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun |
| 2022 | BIBE | Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. | Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun |
| 2022 | BIBE | Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering Approach. | Charles A. Ellis, Martina Lapera Sancho, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun |
| 2021 | BIBE | A Novel Local Explainability Approach for Spectral Insight into Raw EEG-based Deep Learning Classifiers. | Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun |
| 2021 | BIBE | A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers. | Charles A. Ellis, Rongen Zhang, Vince D. Calhoun, Darwin A. Carbajal, Robyn L. Miller, May D. Wang |
| 2021 | BIBE | A Novel Local Ablation Approach for Explaining Multimodal Classifiers. | Charles A. Ellis, Rongen Zhang, Vince D. Calhoun, Darwin A. Carbajal, Mohammad S. Eslampanah Sendi, May D. Wang, Robyn L. Miller |